详解Python使用simplejson模块解析JSON的方法
1，Json模块介绍
JSON(JavaScript Object Notation) 是一种轻量级的数据交换格式。易于人阅读和编写。同时也易于机器解析和生成。它基于JavaScript Programming Language, Standard ECMA-262 3rd Edition - December 1999的一个子集。JSON采用完全独立于语言的文本格式，但是也使用了类似于C语言家族的习惯（包括C, C++, C#, Java, JavaScript, Perl, Python等）。这些特性使JSON成为理想的数据交换语言。
2，Json的格式
2.1,对象:
{name:"Peggy",email:"peggy@gmail.com",homepage:"http://www.jb51.net"}
{ 属性 : 值 , 属性 : 值 , 属性 : 值 }
2.2,数组：
是有顺序的值的集合。一个数组开始于"["，结束于"]"，值之间用","分隔。
[
{name:"Peggy",email:"peggy@gmail.com",homepage:"http://www.jb51.net"}, {name:"Peggy",email:"peggy@gmail.com",homepage:"http://www.jb51.net"},
{name:"Peggy",email:"peggy@gmail.com",homepage:"http://www.jb51.net"}
]
3，Json的导入导出
这里的write/dump的含义是将Json对象输入到一个python_object中，如果python_object是文件，则dump到文件中；如果是对象，则dump到内存中。这是序列化。
3.1，读取Json文件
import simplejson as json
f = file('table.json')
source = f.read()
target = json.JSONDecoder().decode(source)
print target
import simplejson as json
jsonobject = json.load(file('table.json'))
print jsonobject
3.2，显示Json文件
为了显示Json格式好看，原来的Json文件：
[admin@r42h06016.xy2.aliyun.com]$python readJson.py
[{'Query': 'desc zt1;', 'Message': '{"DescibeTableWithPartSpec": "false", "GetTableMetaString":"{\\"tableName\\":\\"zt1\\",\\"owner\\":\\"1365937150772213\\",\\"createTime\\":1346218114,\\"lastModifiedTime\\":0,\\"columns\\":[{\\"name\\":\\"a\\",\\"type\\":\\"string\\"},{\\"name\\":\\"b\\",\\"type\\":\\"string\\"}],\\"partitionKeys\\":[{\\"name\\":\\"pt\\",\\"type\\":\\"string\\"}]}"}', 'QueryID': '', 'Result': 'OK'}]
执行文件：
import simplejson as json
jsonobject = json.load(file('table.json'))
print json.dumps(jsonobject,sort_keys=True,indent=4)
显示：
[admin@r42h06016.xy2.aliyun.com]$python readJson.py
[
{
"Message": "{\"DescibeTableWithPartSpec\": \"false\", \"GetTableMetaString\":\"{\\\"tableName\\\":\\\"zt1\\\",\\\"owner\\\":\\\"1365937150772213\\\",\\\"createTime\\\":1346218114,\\\"lastModifiedTime\\\":0,\\\"columns\\\":[{\\\"name\\\":\\\"a\\\",\\\"type\\\":\\\"string\\\"},{\\\"name\\\":\\\"b\\\",\\\"type\\\":\\\"string\\\"}],\\\"partitionKeys\\\":[{\\\"name\\\":\\\"pt\\\",\\\"type\\\":\\\"string\\\"}]}\"}",
"Query": "desc zt1;",
"QueryID": "",
"Result": "OK"
}
]
3.3,json模块示例：
import json # Converting Python to JSON json_object = json.write( python_object ) # Converting JSON to Python python_object = json.read( json_object )
3.4,simplejson模块 示例：
import simplejson # Converting Python to JSON json_object = simplejson.dumps( python_object ) # Converting JSON to Python python_object = simplejson.loads( json_object )
其中的json_object也可以是文件名比如file(“tmp/table.json”)
4,Json数据的解析
假设对于data.json文件如下：
#test.py
import simplejson as json
ddata = json.loads(file("data.json"))
print ddata
print type(ddata)#<type 'dict'>
其次，我们以读字典中key 为”data”对应的键值
>>> ddata['data'] //查看字典的方法！ >>>type(ddata['data']) <type 'list'>
发现ddata[‘data']是一个列表，列表就要用序号来查询
>>> ddata['data'][0] //查看列表的方法！ >>> type(ddata['data'][0]) <type 'dict'>
ddata[‘data']列表的0号元素是个字典。。
好，那我们查查key为idc的键值是多少
>>> ddata['data'][0]['idc'] //查看字典的方法！ >>> ddata['data'][0]['idc'] //查看字典的方法！ '\xe6\x9d\xad\xe5\xb7\x9e\xe5\xbe\xb7\xe8\x83\x9c\xe6\x9c\xba\xe6\x88\xbf' >>> print ddata['data'][0]['idc'] 杭州德胜机房
5.一些性能讨论
简单测试了一下，如果用JSON，也就是python2.6以上自带的json处理库，效率还算可以：
1K的数据，2.9GHz的CPU，单核下每秒能dump：36898次。大约是pyamf的5倍。但数据量较大，约为pyamf的1.67倍（1101/656）。
start_time: 1370747463.77 loop_num: 36898 end_time: 1370747464.78
再看看simplejson，没有安装C扩展的情况下：
simplejson，没有安装C扩展，跑出的结果让我惊讶：
start_time: 1370748132.87 loop_num: 1361 end_time: 1370748133.88
效率如此之低下。
下面是测试代码：
#! /usr/bin/env python
#coding=utf-8
import time
import json
test_data = {
'baihe': {
'name': unicode('百合', 'utf-8'),
'say': unicode('清新，淡雅，花香', 'utf-8'),
'grow_time': 0.5,
'fruit_time': 0.5,
'super_time': 0.5,
'total_time': 1,
'buy':{'gold':2, } ,
'harvest_fruit': 1,
'harvest_super': 1,
'sale': 1,
'level_need': 0,
'experience' : 2,
'exp_fruit': 1,
'exp_super': 1,
'used': True,
},
'1':{
'interval' : 0.3,
'probability' : {
'98': {'chips' : (5, 25), },
'2' : {'gem' : (1,1), },
},
},
'2':{
'unlock' : {'chips':1000, 'FC':10,},
'interval' : 12,
'probability' : {
'70': {'chips' : (120, 250), },
'20': {'gem' : (1,1), },
'10': {'gem' : (2,2), },
},
},
'one':{
'10,5' :{'id':'m01', 'Y':1, 'msg':u'在罐子里发现了一个银币！',},
'3,7' :{'id':'m02', 'Y':10,'msg':u'发现了十个银币！好大一笔钱！',},
'15,5' :{'id':'m03', 'Y':2, 'msg':u'一只老鼠跑了过去',},
'7,4' :{'id':'m04', 'Y':4, 'msg':u'发现了四个生锈的银币……',},
'2,12' :{'id':'m05', 'Y':6, 'msg':u'六个闪亮的银币！',},
},
}
start_time = time.time()
print "start_time:", start_time
j = 1
while True:
j += 1
a = json.dumps(test_data)
data_length = len(a)
end_time = time.time()
if end_time - start_time >= 1 :
break
print "loop_num:", j
print "end_time: ",end_time
print data_length ,a
总结：python自带的json，性能可以接受。simplejson，如果没有C扩展加速，效率极其低下。
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